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Title: Studying the effect of meteorological factors on the SO2 and PM10 pollution levels with refined versions of the SARIMA model

Numerous time series methods are used in environmental sciences allowing the detailed investigation of air pollution processes. The goal of this study is to present the empirical analysis of various aspects of stochastic modeling and in particular the ARIMA/SARIMA methods. The subject of investigation is air pollution in the town of Kardzhali, Bulgaria with 2 problematic pollutants – sulfur dioxide (SO2) and particulate matter (PM10). Various SARIMA Transfer Function models are built taking into account meteorological factors, data transformations and the use of different horizons selected to predict future levels of concentrations of the pollutants.
Authors:
; ;  [1] ;  [2]
  1. Department of Applied Mathematics and Modeling, Faculty of Mathematics and Informatics, Paisii Hilendarski University of Plovdiv, 24 Tzar Assen str., 4000 Plovdiv (Bulgaria)
  2. Department of Physics, Technical University – Plovdiv, 25 Tzanko Djusstabanov str., 4000 Plovdiv (Bulgaria)
Publication Date:
OSTI Identifier:
22492620
Resource Type:
Journal Article
Resource Relation:
Journal Name: AIP Conference Proceedings; Journal Volume: 1684; Journal Issue: 1; Conference: AMiTaNS'15: 7. international conference for promoting the application of mathematics in technical and natural sciences, Albena (Bulgaria), 28 Jun - 3 Jul 2015; Other Information: (c) 2015 AIP Publishing LLC; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; AIR POLLUTION; BULGARIA; COARSE PARTICLES; CONCENTRATION RATIO; METEOROLOGY; POLLUTANTS; SIMULATION; STOCHASTIC PROCESSES; SULFUR DIOXIDE; TRANSFER FUNCTIONS